DESCRIPTION (provided by candidate): The long term goal of this application is to train the candidate in neuroscience in order to become a leading member of a multidisciplinary team. This would enable the candidate to become a co-investigator on imaging projects and better understand the science that she is trying to model statistically. The ultimate task to undertake in this application is to statistically merge the results from multiple brain imaging modalities to form one clearer picture of the, brain. This project is very important in that there are many researchers who use brain imaging techniques to try to better understand the normal and impaired functioning of the brain. This will be achieved by the following three specific aims: 1) for the applicant to obtain training in several areas of neuroscience 2) the applicant will investigate several methods to independently analyze data obtained from Magnetic Resonance Sectroscopy (MRS) 3} the applicant will merge the results from these three particular modalities. Specific aim 1 will be achieved through the applicant taking eight graduate level courses in neuroscience as well as reading journal articles provided by her mentor team. Specific aim 2 will be addressed through the applicant working with her mentors to compare many different statistical methods to analyze the data from MRS, collected from a current ongoing study. Traditional methods as well as untraditional methods such as cluster analysis, Generalized Linear Mixed Effects Models (GLMM), and kth nearest neighbor will be compared to find the best method. In order to address specific aim three, individual subjects will be imaged on all three modalities that are available at the Hoglund Brain Imaging Center. The goal of this specific aim is to combine all three datasets into one clear picture. In order to analyze this data, the applicant will begin with pair wise combinations. Then, she will add the third data set to the already combined pair. Finally, she will compare the three different ways that the pair wise combinations could have been achieved to determine which method provides the most accurate result.